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        David Menninger's Analyst Perspectives

        In this analyst perspective, Dave Menninger takes a look at data lakes. He explains the term “data lake,” describes common use cases and shares his views on some of the latest market trends. He explores the relationship between data warehouses and data lakes and share some of Ventana Research’s findings on the subject. He also provides an assessment of the risks organizations face in working with data lakes and offers recommendations for maximizing the potential of data.

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        Topics: Big Data, Data Warehousing, Analytics, Business Analytics, Business Intelligence, Data Governance, Data Management, Data Preparation, data lakes

        Teradata recently held its annual Partners conference, at which gather several thousand customers and partners from around the world. This was the first Partners event since Vic Lund was appointed president and CEO in May. Year on year, Teradata’s revenues are down about 5 percent, which likely prompted some changes at the company. Over the past few years Teradata made several technology acquisitions and perhaps spread its resources too thin. At the event, Lund committed the company to a focus...

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        Topics: Big Data, Teradata, Analytics, Business Analytics, Business Intelligence, Cloud Computing, Information Management

        Ventana Research has newly published its Mobile Analytics and Business Intelligence 2016 Value Index. The Value Index provides a comprehensive evaluation of vendors and their product offerings across seven categories. In performing that analysis, I realized that this software category is at a crossroads. Once an optional capability often reserved for executives, mobile analytics is becoming a requirement of business users across organizations. The blurring of lines between work and personal...

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        Topics: Mobile, Analytics, Business Analytics, Business Intelligence

        It’s part of my job to cover the ecosystem of Hadoop, the open source big data technology, but sometimes it makes my head spin. If this is not your primary job, how can you possibly keep up? I hope that a discussion of what I’ve found to be most important will help those who don’t have the time and energy to devote to this wide-ranging topic.

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        Topics: Big Data, Microsoft, Teradata, Business Analytics, Business Intelligence, IBM, Information Management, Operational Intelligence, Oracle, HPE, ODPI, Strata+Hadoop

        Data virtualization is not new, but it has changed over the years. The term describes a process of combining data on the fly from multiple sources rather than copying that data into a common repository such as a data warehouse or a data lake, which I have written about. There are many reasons for an organization concerned with managing its data to consider data virtualization, most stemming from the fact that the data does not have to be copied to a new location. It could, for instance,...

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        Topics: Big Data, Business Analytics, Business Intelligence, Data Integration, Data Lake, Information Applications, Information Management, Data Virtualization

        Predictive analytics is a rewarding yet challenging subject. In our benchmark research on next-generation predictive analytics at least half the participants reported that predictive analytics allows them to achieve competitive advantage (57%) and create new revenue opportunities (50%). Yet even more participants said that users of predictive analytics don’t have enough skills training to produce their own analyses (79%) and don’t understand the mathematics involved (66%). (In the term...

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        Topics: Data Science, Business Analytics, Business Intelligence, Business Performance, Cloud Computing, Uncategorized

        Qlik helped pioneer the visual discovery market with its QlikView product. In some respects, Qlik and its competitors also spawned the self-service trend rippling through the analytics market today. Their aim was to enable business users to perform analytics for themselves rather than building a product with the perfect set of features for IT. After establishing success with end users the company began to address more of the concerns of IT, eventually creating a robust enterprise-grade...

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        Topics: Analytics, Business Analytics, Business Collaboration, Business Intelligence, Cloud Computing, Data Preparation, Information Management, Uncategorized, Visualization, Qlik, Qlik Sense

        It has been more than five years since James Dixon of Pentaho coined the term “data lake.” His original post suggests, “If you think of a data mart as a store of bottled water – cleansed and packaged and structured for easy consumption – the data lake is a large body of water in a more natural state.” The analogy is a simple one, but in my experience talking with many end users there is still mystery surrounding the concept. In this post I’d like to clarify what a data lake is, review the...

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        Topics: Big Data, Data Science, Predictive Analytics, Social Media, Business Analytics, Business Intelligence, Data Governance, Data Lake, Governance, Risk & Compliance (GRC), Information Management, Uncategorized, Strata+Hadoop

        I recently attended the SAS Analyst Summit in Steamboat Springs, Colo. (Twitter Hashtag #SASSB) The event offers an occasion for the company to discuss its direction and to assess its strengths and potential weaknesses. SAS is privately held, so customers and prospects cannot subject its performance to the same level of scrutiny as public companies, and thus events like this one provide a valuable source of additional information.

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        Topics: Big Data, Predictive Analytics, SAS, Analytics, Business Analytics, Business Collaboration, Business Intelligence, Business Performance, Information Applications, Information Management, Uncategorized, Visualization

        Last week I attended Spark Summit East 2016 at the New York Hilton Midtown. It revealed several ways in which Spark technology might impact the big data market.

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        Topics: Big Data, Analytics, Business Analytics, Business Intelligence, In-memory, Information Applications, Information Management, Operational Intelligence, Uncategorized
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        Our Analyst Perspective Policy

        • Ventana Research’s Analyst Perspectives are fact-based analysis and guidance on business, industry and technology vendor trends. Each Analyst Perspective presents the view of the analyst who is an established subject matter expert on new developments, business and technology trends, findings from our research, or best practice insights.

          Each is prepared and reviewed in accordance with Ventana Research’s strict standards for accuracy and objectivity and reviewed to ensure it delivers reliable and actionable insights. It is reviewed and edited by research management and is approved by the Chief Research Officer; no individual or organization outside of Ventana Research reviews any Analyst Perspective before it is published. If you have any issue with an Analyst Perspective, please email them to ChiefResearchOfficer@ventanaresearch.com

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